1 citations · 1 across the 4 of their papers we have counts for
6 papers
Xmodel-2.5: 1.3B Data-Efficient Reasoning SLM
Yang Liu, Xiaolong Zhong, Ling Jiang
Large language models deliver strong reasoning and tool-use skills, yet their computational demands make them impractical for edge or cost-sensitive deployments. We present \textbf…
MemOrb: A Plug-and-Play Verbal-Reinforcement Memory Layer for E-Commerce Customer Service
Yizhe Huang, Yang Liu, Ruiyu Zhao +3
Large Language Model-based agents(LLM-based agents) are increasingly deployed in customer service, yet they often forget across sessions, repeat errors, and lack mechanisms for con…
Survey of Specialized Large Language Model
Chenghan Yang, Ruiyu Zhao, Yang Liu +1
The rapid evolution of specialized large language models (LLMs) has transitioned from simple domain adaptation to sophisticated native architectures, marking a paradigm shift in AI…
MindFlow: Revolutionizing E-commerce Customer Support with Multimodal LLM Agents
Ming Gong, Xucheng Huang, Chenghan Yang +4
Recent advances in large language models (LLMs) have enabled new applications in e-commerce customer service. However, their capabilities remain constrained in complex, multimodal…
Digital Player: Evaluating Large Language Models based Human-like Agent in Games
Jiawei Wang, Kai Wang, Shaojie Lin +11
With the rapid advancement of Large Language Models (LLMs), LLM-based autonomous agents have shown the potential to function as digital employees, such as digital analysts, teacher…
Xmodel-1.5: An 1B-scale Multilingual LLM
Wang Qun, Liu Yang, Lin Qingquan +1
We introduce Xmodel-1.5, a 1-billion-parameter multilingual large language model pretrained on 2 trillion tokens, designed for balanced performance and scalability. Unlike most lar…